FINAL WORD
just hit the market . This combination of first principles simulation and AI ( white box and black box models respectively ) offers the best of both worlds : modeling assets and processes almost in real time to improve system design and also get the most out of operational performance . One of the ways it works is by allowing AI models to integrate with traditional physics-based simulation through a drag-and-drop user interface . AI often runs faster than physics-based models and requires fewer adjustments to set up . As a result , companies can get models up and running quickly , while using less CPU capacity and therefore requiring a smaller carbon footprint .
What benefits does AI bring to industries ?
Industrial AI solutions contextualize key performance and sustainability data with Artificial Intelligence and human knowledge . As a result , companies can unlock value and sustainability gains in many ways , now and in the future .
In the energy sector , AI technologies are supporting the transition to renewable energies . The Italian multinational Enel has committed to decarbonizing its energy mix by 2040 . It has already installed over 50 GW of renewable capacity . To accelerate the transition , Enel has deployed AI-based asset performance management software along with predictive analytics . Data silos have been eliminated , accelerating decisionmaking and offering efficiencies across the business ecosystem . The energy leader can now predict asset failures and ensure a constant energy supply , and is on track to achieve a fully autonomous plant .
Similarly , another global energy company
is using predictive asset optimization to improve reliability and reduce maintenance costs . Just one capture helped detect a performance anomaly in the heat recovery pipes of a cogeneration unit five months in advance , saving significant costs . Since 2019 , the software has detected over 1,700 asset performance anomalies . More than US $ 37 million has been saved , unplanned downtime has been reduced , and resource usage has been reduced , improving the environmental impact .
AI is generating similar benefits in other hard-to-reduce sectors , such as cement , which generates 6 % of all man-made emissions . Oyak Cement , whose operations extend from Turkey to Portugal , Cape Breton and West Africa , uses an edge-to-cloud data management system infused with
The industrial world is now entering what has been called an AI revolution .
AI to replace 30 % of its energy from fossil fuels with renewable sources , as well as to reduce energy use . For every 1 % reduction in energy used , the company saves between five and seven million euros . With real-time information at hand , it also reduces CO 2 emissions , ensuring regulatory compliance .
On a more fundamental level , AI is helping increase resilience to the worst effects of climate change . With rising global temperatures , the city of Salem , Oregon , in the Pacific Northwest , has witnessed more outbreaks of toxic algal blooms in lakes and catchment rivers . With the help of a native cloud and multi-tenant data management platform , city authorities have aggregated multiple data sources , from algae levels to water depth and weather and satellite data , into a central hub . Intelligent predictive insights now alert them to increased algae and cyanotoxin activity two weeks before they occur , allowing teams to preserve water quality , safeguard ecosystems , and ensure that Salem ’ s five million residents have safe drinking water .
Industrial AI is essential for the transition to sustainability
The industrial world is now entering what has been called an AI revolution .
Viewing AI simply as a tool to increase profits is to severely underestimate – and underutilize – the capabilities of this powerful science . As industrial companies work to integrate sustainability into the core of their operations , AI can empower them to align business success with environmental responsibility .
AI will not solve the climate crisis , but it can generate greater value for industries while improving sustainability , although success in each case requires time and effort and depends on how technologies are applied .
However , in general , the union of sustainability and profitability is no longer a difficult goal to achieve . With its capabilities to optimize processes , improve efficiency , and promote green practices , AI serves as a binding element that brings these seemingly separate goals together to create the future we need . •
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